Call For Paper Volume:7 Issue:1 Jan'2020 |

IoT framework for improving fall-detection remedial and preventive measures in wide-area

Publication Date : 30/05/2019


DOI : 10.21884/IJMTER.2019.6017.EGM9B

Author(s) :

Matta. Jagadeesh Chandra Prasad , P. Siddaiah.


Volume/Issue :
Volume 6
,
Issue 5
(05 - 2019)



Abstract :

About one third of the senior population over the age of 65 falls each year, but since many incidents go unreported by seniors and unrecognized by family members or caregivers – this estimate is most likely quite low. For seniors who fall and are unable to get up on their own, the period of time spent immobile often affects their health outcomes. With growing number of small working families the issue of fall detection and remedy is becoming major healthcare issue worldwide. As the numbers grow the need of prevention and locality based support is warranted. Many wearable healthcare devices for fall detection have been proposed. Most of these devices are based on wireless technologies and smart interface. Some researchers have proposed the use of big data analytics and cloud services to for data collection framework. With the help of data collection framework the post-fall detection remedial procedures can be effectively implemented. In the next step toward improving health care conditions the data collection can be used to model, predict and control the alert as well as prevent elderly fall conditions. An IoT and big data analytics based framework is proposed to define the prioritized alert messaging service to contact the nearest able professional after fall detection. To improve the report and action procedure the data of patients and related attendants are segregated based on geo-location, gender, family work place location, attendant location, emergency center location, patient medical history and other related factors. The implementation architecture and results from cloud services are presented. It is shown that by finding co-relation between patient’s history and geo-location the time between fall-detection and arrival of assistance can be significantly improved. With immediate professional response the recovery time and health care expenses can be reduced significantly. Implantation results show that the proposed scheme can be effectively employed in a local community as well as wide-area network for effective application of fall-detection remedial and preventive measures. Index Terms—Big Data, decision tree learning algorithm, elderly people, Fall detection, Internet-of-Things, Smart IoT Gateway, wearable sensor.


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IoT framework for improving fall-detection remedial and preventive measures in wide-area

May 24, 2019